Scientific Computing. Vol. II, Eigenvalues and optimization
- 作者： Trangenstein, John A., author.
- 其他作者：
- 其他題名：
- Eigenvalues and optimization
- Texts in computational science and engineering ;
- 出版： Cham : Springer International Publishing :Imprint: Springer
- 叢書名： Texts in computational science and engineering,19
- 主題： Eigenvalues. , Mathematical optimization. , Computer science--Mathematics. , Mathematics. , Computational Mathematics and Numerical Analysis. , Ordinary Differential Equations. , Optimization.
- ISBN： 9783319691077 (electronic bk.) 、 9783319691060 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: 1. Eigenvalues and Eigenvectors -- 2. Iterative Linear Algebra -- 3. Nonlinear Systems -- 4. Constrained Optimization -- References -- Author Index.
- 摘要註: This is the second of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses more advanced topics than volume one, and is largely not a prerequisite for volume three. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 49 examples, 110 exercises, 66 algorithms, 24 interactive JavaScript programs, 77 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative linear algebra.
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讀者標籤：
- 系統號： 005413463 | 機讀編目格式
館藏資訊
This is the second of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses more advanced topics than volume one, and is largely not a prerequisite for volume three. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 49 examples, 110 exercises, 66 algorithms, 24 interactive JavaScript programs, 77 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative linear algebra.